Operation and maintenance multi-mode decision making system framework based on multi-core heterogeneous processor

Abstract

The invention discloses an operation and maintenance multi-mode decision making system framework based on a multi-core heterogeneous processor. Data of operation and maintenance environment is acquired through sensors and cameras, multi-mode decision making is conducted by the multi-core heterogeneous processor, decision making information is transferred to a control unit through a bus, and a management platform, early warning and prevention are controlled by the control unit, so that automatic early warning and prevention of accidents are achieved.

Description

technical field [0001] The invention relates to an operation and maintenance multi-modal decision-making system architecture based on a multi-core heterogeneous processor Background technique [0002] With cloud computing and virtualization, showing the characteristics of "large scale", "high density", "high energy consumption" and "complexity", the construction and development of a new generation of data centers and the improvement of data center infrastructure management will become increasingly Importantly, the infrastructure integration management and intelligence of the data center will become a new trend in the development of the data center. [0003] At present, O&M lacks automation methods, passive O&M, low efficiency, and large-scale IT facilities bring management pressure. It is necessary to realize the automatic monitoring of the data center, improve the timely alarm capability of system and environmental parameters, and improve the response speed and monitoring ...

AI Technical Summary

Problems solved by technology

Heterogeneous computing has received more attention in recent years, mainly because the traditional method of increasing computing power by increasing the CPU clock frequency and the number of cores has encountered heat dissipation and energy consumption bottlenecks

Although dedicated computing units such as GPUs have low operating frequency, more cores and parallel computing capabilities, the overall performance / chip area ratio and performance / power consumption ratio are high, but they are far from being fully utilized.

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